Zakria Khan
Full Stack Developer
Full Stack Developer & AI/ML Engineer. Specialized in Next.js, the MERN stack, and Generative AI (RAG & LLMs). IBM Certified.
About Me
I am a Full Stack Developer and AI/ML Engineer based in Pakistan, who loves building at the intersection of robust web development and intelligent data-driven software. With an IBM Full Stack Software Developer Certification and practical experience spanning enterprise web applications and advanced machine learning, I focus on creating applications that are both highly performant and contextually smart. My toolkit bridges the best of both frontend frameworks like React and Next.js, scalable backend architectures using Node.js, Express, and Python (FastAPI/Flask), and cutting-edge AI implementations featuring LangChain, RAG pipelines, and LLMs.
Key Highlights
- Full-Stack Engineering: Proficient in the MERN stack and Next.js. Experienced in building enterprise-grade tools, reusable component libraries, and optimizing page load speeds.
- Generative AI & ML: Hand-on experience engineering Retrieval-Augmented Generation (RAG) workflows, crafting precise prompt engineering, fine-tuning transformer models, and deploying production-ready interactive apps via Streamlit.
- Architecture & DevOps: Experienced with RESTful/GraphQL APIs, database management (MongoDB, PostgreSQL), and containerization with Docker to ensure smooth, continuous delivery in Agile environments.
Experience
AI/ML Engineering Intern
DevelopersHub Corporation
Worked on Machine Learning, Data Science, and Generative AI projects involving predictive modeling, natural language processing, conversational AI, and end-to-end ML pipelines. Developed and evaluated AI solutions using modern machine learning frameworks, transformer models, and retrieval-augmented generation techniques while building deployable applications for real-world use cases.
Key Achievements
- → Performed exploratory data analysis and visualization on real-world datasets using Python, Pandas, Matplotlib, and Seaborn to identify trends, distributions, and feature relationships
- → Developed stock price forecasting models using Yahoo Finance data, applying Linear Regression and Random Forest algorithms for short-term price prediction
- → Built and evaluated heart disease prediction systems using feature engineering, classification models, ROC-AUC analysis, confusion matrices, and feature importance techniques
- → Designed AI-powered healthcare chatbots using Large Language Models (LLMs), incorporating prompt engineering, API integrations, response safety mechanisms, and conversational workflows
- → Fine-tuned BERT-based transformer models for news topic classification using transfer learning, achieving robust performance through text preprocessing and model evaluation
- → Implemented end-to-end machine learning pipelines with Scikit-learn Pipeline API, including preprocessing, hyperparameter tuning with GridSearchCV, and model serialization
- → Developed Retrieval-Augmented Generation (RAG) applications using LangChain, vector embeddings, document retrieval, and memory-aware conversational systems
- → Deployed machine learning and generative AI applications through Streamlit and Gradio, enabling interactive model inference and chatbot experiences
Software Development Intern
AlphaTech Software House
Contributed to the development of enterprise web applications in an Agile environment, focusing on wholesale management and e-commerce solutions. Collaborated with cross-functional teams to build scalable frontend features, improve development workflows, and enhance application performance.
Key Achievements
- → Engineered a wholesale management system with 6+ core modules, automating invoicing processes and reducing processing time by approximately 90%
- → Developed a library of 6+ reusable React.js components for an e-commerce platform, improving maintainability and reducing page load times by 30%
- → Implemented Git branching strategies and participated in peer code reviews, improving team collaboration and supporting on-time sprint delivery
Featured Projects
RAG Chatbot
A conversational chatbot that remembers context and retrieves external information using Retrieval-Augmented Generation (RAG) with LangChain, ChromaDB, local BGE embeddings, and Google Gemini 2.5 Flash.
YC Directory - Startup Pitching Platform
YC Directory is a full-stack web application that allows users to pitch their startups, browse other innovative ideas, and connect with fellow entrepreneurs. It's built with Next.js, Sanity, and NextAuth, providing a seamless and interactive experience for showcasing and discovering new ventures.
Other Projects
ResuMatch
ResuMatch is a smart, AI-powered application designed to help job seekers optimize their resumes. It provides detailed feedback, an Applicant Tracking System (ATS) score, and actionable suggestions to improve the chances of landing a dream job. The application is built on the Puter.com platform, leveraging its AI, authentication, and storage capabilities.